Methods and systems for color flow dynamic frame persistence

ABSTRACT

Methods and systems for color flow dynamic frame persistence in ultrasonic imaging are provided.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of Chinese Patent Application No.201010042708.5, filed on Jan. 5, 2010, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

This application relates to ultrasonic imaging technology.

SUMMARY OF THE INVENTION

Disclosed herein are embodiments of methods and systems for color flowdynamic frame persistence in ultrasonic imaging.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of a method for color flow dynamic framepersistence;

FIG. 2 is a flowchart of a method for calculating the blood vesseldirection of the flow velocity image;

FIG. 3 is a schematic view of calculating the blood vessel direction;

FIG. 4 is a flowchart of a method for calculating the blood vesseldirection of the flow velocity image;

FIG. 5 is a schematic view illustrating a computation method of bloodvessel direction based on morphology;

FIG. 6 is a schematic view illustrating judgment of flow movementdirection;

FIG. 7 is a schematic view of flow offset;

FIG. 8 is a block diagram of a color ultrasonic system;

FIG. 9 is a block diagram of a system for color flow dynamic framepersistence;

FIG. 10 is a block diagram of a system for calculating blood vesseldirection of flow velocity image; and

FIG. 11 is a block diagram of a system for calculating blood vesseldirection of flow velocity image.

DETAILED DESCRIPTION

Ultrasonic instruments, which are generally used in observing the tissueand structure of human body, have become crucial in medical diagnosisowing to their security, convenience, non-destruction (of tissue), andlow cost. Color flow imaging technology uses the Doppler Effect todetect the existence of blood flow in human body and estimate thekinetic parameters of the flow.

In the process of color frame persistence, the SNR (Signal to NoiseRatio) of signal detection can be raised with the amount of time, suchthat the sensitivity for detecting faint flow signals can be improved.Typically, the operation of frame persistence is generally taken at thesame position of previous and current frames, without considering thefluidity factor of flow. As there is a certain time interval Δt betweenthe current frame and the previous frame, when calculating the flow atthe current frame (i, j), the flow at the previous frame has alreadymoved forward a certain distance along the blood vessel. If framepersistence is applied to the same position of flow between the currentframe and the previous frame, the important fact that blood is flowingis ignored, and the fluidity of blood flow cannot be reflected.

According to one aspect of the disclosure, a method for calculatingblood vessel direction of a flow velocity image includes distinguishingeach of the points in the flow velocity image as points in a flow regionand points in a background region. The method also includes estimating arough direction of a computing point by setting a plurality ofdirections and respectively calculating the number of points in the flowregion connecting with the computing point in each direction, and takingthe direction with the maximum number of points as the rough directionof the computing point. The method further includes determiningmidpoints on the direction vertical to the rough direction in aneighborhood, and taking a line connecting the midpoints as a medianline of the blood vessel in the neighborhood, wherein the neighborhoodis centered on the computing point and includes a plurality of points inthe flow region on the rough direction. The method also includescalculating the direction of the blood vessel on the computing pointaccording to the determined median line of the blood vessel.

According to another aspect, a system for calculating blood vesseldirection of a flow velocity image includes a distinguishing moduleconfigured to distinguish each of the points in the blood flow velocityimage as points in a flow region and points in a background region. Thesystem also includes an estimation module configured to set a pluralityof directions and respectively calculate the number of the points in theflow region connecting with the computing point in each direction, andtake the direction with the maximum number as the rough direction of thecomputing point. The system further includes a determination moduleconfigured to determine midpoints on the direction vertical to the roughdirection in a neighborhood, and take the line connecting the midpointsas the median line of the blood vessel in the neighborhood, wherein theneighborhood takes the computing point as center and comprises aplurality of points in the flow region on the rough direction. Thesystem also includes a computation module configured to calculate thedirection of the blood vessel on the computing point according to thedetermined median line of the blood vessel.

According to still another aspect, a system for calculating blood vesseldirection of a flow velocity image includes a distinguishing moduleconfigured to distinguish each of the points in the flow velocity imageas points in a flow region and points in a background region. The systemalso includes an extraction module configured to extract a skeleton ofthe flow region from the distinguished image. The system furtherincludes a computation module configured to calculate the direction ofeach point of the skeleton according to a plurality of neighbor pointsof each computing point of the skeleton.

According to yet another aspect, a system for color flow dynamic framepersistence includes an acquisition module configured to acquire aresult of a previous frame persistence and current flow velocity image.The system also includes a computation module configured to calculate ablood vessel direction reflected by the result of the previous framepersistence. The system further includes an offset module configured tooffset the result of previous frame persistence along the direction of ablood vessel with flow direction and flow velocity. The system alsoincludes a persistence module configured to implement frame persistencebetween the current flow velocity image and the offset result of theprevious frame persistence.

Referring to FIG. 1, a method for color flow dynamic frame persistencemay include an acquisition step 100, a third computation step 102, anoffset step 104, and a persistence step 108. The method may also includean interpolation step 106.

According to one embodiment, the method for color flow dynamic framepersistence comprises: acquiring the result F_(i-1) of the previousframe persistence and the current flow velocity image I_(i) (step 100);calculating the direction of the blood vessel reflected by F_(i-1),which includes calculating the blood vessel direction of each point inthe flow region (step 102); making an offset for F_(i-1) by using theblood vessel direction, the flow direction and the flow velocity (step104); after the offset is done, carrying out the frame persistenceφ(I_(i),F_(i-1)) for F_(i-1) and I_(i); thus obtaining the result F_(i)of the ith frame persistence.

The blood vessel direction is not about the positive or negative flowvelocity; instead, it is about the flowing path of the blood flows inthe blood vessel, and the blood flows along the flowing path. The bloodvessel direction identifies the shape structure of the blood vessel.Generally, the blood vessel direction is considered approximatelyparallel to the blood vessel wall. When calculating the blood vesseldirection, the direction of each point in the flow region needs to becalculated. The blood vessel direction can be determined by utilizingimage processing methods with the spatial structure of blood vessel.

In one embodiment, the blood vessel direction can be calculated by usinga first distinguishing step 200, an estimation step 202, a determinationstep 204, and a first computation step 206, as illustrated in FIG. 2.This may be accomplished by first, estimating the rough direction of thecalculating point located in the blood vessel, then narrowing thecalculation range, and accurately calculating the blood vessel directionin a small range. An example of the process is described below.

1. The image distinguishing (step 200) is used to distinguish which partof the image is the flow region or the background region. For example,by binarizing the input result F_(i-1) of the previous framepersistence, each point in the flow velocity image can be distinguishedas point in the flow region or point in the background region. Thebinarization can be done with a threshold, that is, marking the pointswhose absolute value are smaller than a threshold as zero and theremaining points as 1. Additionally, the points in the image (F_(i-1))can be directly distinguished as points in the flow region and points inthe background region with a predefined threshold.

2. Rough estimation of blood vessel direction may then be performed. Theestimation can be done by setting the number of directions in roughestimation according to requirement for the accuracy of the system. Twodirections including the vertical and horizontal directions can be set;or four directions including the directions of 0°, 45°, 90° and 135° canbe set. If necessary, even eight directions can be set. One embodimentincludes setting two directions, respectively calculating the number ofthe points consequently connected with the computing point in eachdirection, and taking the direction with the maximum number as the roughdirection of the computing point in the flow region (step 202).

FIG. 3 is a schematic view of calculating blood vessel direction, inwhich all of the blocks comprise a binary image. The value of the blackblock is equal to 1, and the white to 0. In this embodiment, the blackblocks stand for the flow region and the white blocks stand forbackground region. Given “★” as the computing point, there are sixpoints in the flow region connected to the computing point in thehorizontal direction (including the computing point itself), and threepoints in the flow region in the vertical direction (including thecomputing point itself); thus the rough direction of the computing pointis the horizontal direction.

3. Accurate computation of blood vessel direction may then be performed,which is based on the rough estimation of blood vessel direction. Anaccurate computation is applied to the blood vessel direction withspatial relations between points in current flow region and points inthe neighborhood. The specific steps will be further described herein.Firstly, the neighborhood of the computing point is determined, whereinthe neighborhood takes the computing point as center and includes aplurality of points in the flow region in the rough direction of thecomputing point. Secondly, the median line of the blood vessel in theneighborhood is determined. To each point in the neighborhood, midpointsof the blood vessel are counted along the direction which is vertical tothe rough direction of the blood vessel. The lines connecting thesemidpoints comprise the median line of the blood vessel in theneighborhood. In the embodiment as shown in FIG. 3, the rough directionof “★” is the horizontal direction. Given the computing neighborhoodtake the “★” as center and three pixels respectively in the left andright sides. The “∘” shown in FIG. 3 is the midpoint of the blood vesselin the neighborhood. The white solid lines lined up by these midpointsare regarded as the median line of the blood vessel in the neighborhood(step 204).

With the median line of the blood vessel, a linear fitting or HoughTransform can be applied to obtain the direction of the blood vessel(step 206). As shown in FIG. 3, the white dotted line is the fittedline. The angle θ between the blood vessel direction of “★” and thehorizontal direction can be calculated according to the slope of thestraight line.

The binarization of the image is used for convenience. The step, whichdistinguishes the flow region and the background region, is notnecessary at the beginning. The distinguishing step can be used todistinguish the current point is background or flow in other steps.

In one embodiment, the blood vessel direction is calculated based onmorphological characteristics, which comprises a second distinguishingstep 400, an extraction step 402, and a second computation step 404, asillustrated in FIG. 4. The blood vessel direction is calculated with theskeleton extracted by morphology, wherein the skeleton is used toexpress the shape and structure of a flat region with a simplifieddiagram. The detailed process is as follow:

1. The Image distinguishing (step 400) is performed, which is similar tostep 200.

2. Extracting the skeleton of the distinguished image (step 402) is alsopreformed. Additionally, before extracting the skeleton, a preprocess,such as denoising and edge smoothing, can be applied to thedistinguished binarization image so as to deburr the extracted skeletonfor achieving a best effect.

3. Calculating the direction of each point on the skeleton may befurther performed. The skeleton includes a plurality of lines, so thedirection of the point on the skeleton can be calculated by utilizingmethod of linear fitting or Hough transform to a plurality of neighborpoints (step 404).

Additionally, to calculate the point not on the skeleton, as theskeleton is a simplification of a flat region, the direction of thepoint of the skeleton is regarded as the direction of points not on theskeleton, wherein the point of the skeleton is nearest to the points noton the skeleton and can be lined up in the blood flow region in thedistinguished image.

FIG. 5 is a schematic view of computing blood vessel direction based onthe skeleton, in which the curve/is the deburred skeleton, point A isthe computing point, point B is the nearest point to point A on theskeleton, the dotted line is the direction of point B, thus thedirection of point B can be regarded as the direction of point A.

Additionally, the direction of the blood vessel can be calculated withgradient properties, wherein the gradient properties are about thevelocity or energy at the center of blood vessel being higher than thatat the both sides and degression on both sides in the velocity image orenergy image. A skilled artisan will appreciate that the algorithms usedin calculating the blood vessel direction include, but are not limit tothe described methods herein. Various methods, which are used in dynamicframe persistence by calculating blood vessel direction, may also beused.

In the described embodiments, the blood vessel direction is calculatedwith the result of the previous frame persistence. It can be understoodby those skilled in the art that the flow directions are identicalwithout any change in each of the flow velocity image series or eachframe persistence result. Therefore, similarly, the blood vesseldirection can be calculated with current frame persistence or otherprevious frame persistence, and should not be limited in with previousframe persistence.

After determining the blood vessel direction, the result F_(i-1) ofprevious frame persistence needs to be offset (step 104). Theinformation about blood vessel direction and flow direction is neededwhen offset. The information about the shape and structure of bloodvessel can be identified by the blood vessel direction. However, thedirection along which the blood flows cannot be judged. The flowdirection can be obtained with Doppler properties; that is, if the flowvelocity is positive, the blood flows towards to the transducer,whereas, if the flow velocity is negative, the blood flows away from thetransducer.

With the information about the directions of blood vessel and the flow,the movement direction of flow can be judged. An example is shown inFIG. 6, in which the velocity of point A is negative, which means theblood flows away from the transducer. According to the blood vesseldirection, the movement direction of point A is judged as V₁. Similarly,the velocity of point B is positive, which means the blood flow towardthe transducer. According to the blood vessel direction, the movementdirection of point B is judged as V₂.

The offset can be obtained by velocity. The larger the velocity, thelarger the offset, whereas, the smaller the velocity, the smaller theoffset. The relationship between the offset tran and the velocity V canbe expressed with a function tran=ƒ(V), where the function f can be setwith actual needs. The function f can be linear function or quadraticfunction, as long as it meets the requirement of the larger the flow,the larger the offset.

For example, the relation between the offset tran and the velocity V canbe expressed with a function tran=V×S/(128×fp), where fp is frame rate,S is the Scale set by user, V×S/128 is the flow velocity detected, 1/fpis the interval between two adjacent frames, thus V×S/(128×fp) is thedistance of flow between two moments of two frames.

A skilled artisan will appreciate that, by multiplying the flow velocityV with the interval of the two frames, the distance of flow between twomoments of two frames is obtained, and the distance is regarded as theoffset.

Due to the angle of emission and other reasons, the velocity detected byan ultrasonic instrument under C mode is generally not the real flowvelocity. Therefore, the formula can be transformed according to actualsituations. For example, the formula can be tran=k×V×S/(128×fp)+b, wherek is a constant set with actual needs, the contract between high speedflow and low speed flow can be raised when k>1, while the flow velocitytrends to consistent when k<1. To get the effect, the formula can betransformed with double transform, log transform, Gamma transform, etc.However, no matter what transform method, it needs to meet therequirement that the higher the flow velocity, the larger the offset.

Having such described information, the result of the previous framepersistence can be offset. In one embodiment, the detailed process is asfollows.

1. Decomposing offset with the blood vessel direction. The offset tranis decomposed in the horizontal and vertical directions, respectively,according to the blood vessel direction. After decomposition, the offsetcan be expressed as (Δi,Δj) where Δi=tran cos θ, Δj=tran sin θ and θ isthe angle between the directions of blood vessel and horizon.

2. Offsetting velocity image with the decomposed offsets. Afterobtaining the horizontal and vertical offsets, the point is offset adistance (Δi,Δj) along the flow direction. FIG. 7 shows an example of anoffset, in which the point A is offset (Δi,Δj) along the blood vesseldirection according to the flow direction, and the point A′ is obtained.

Additionally, as the offsets of each point in the flow region might notbe identical, a plurality of points in the flow region might be offsetto a same point after offset, which will lead to some points in the flowregion have no value after offset. In such case, an interpolation can beutilized (step 106). The method of interpolation can be used accordingto practical situations.

After offsetting the result of previous frame persistence, the offsetresult is still marked as F_(i-1), an operation of frame persistence isapplied to F_(i-1) and I_(i) to obtain the result F_(i)=φ(I_(i),F_(i-1))of current frame persistence (step 108). The result of the current framepersistence is processed by other signal processing techniques shown inFIG. 8, and finally sent to a display. With the frame persistenceaccording to the described embodiment, the flow displayed shows theblood flows along the blood vessel direction, and more satisfies theprinciple of hemodynamics.

As illustrated in FIG. 9, a system for color flow dynamic framepersistence may include an acquisition module 900, a third computationmodule 902, an offset module 904 and a persistence module 908. Aninterpolation module 906 may also be included in some embodiments. Theacquisition module 900 is configured to acquire the result of previousframe persistence of the flow velocity image, as well as the currentflow velocity image. The third computation module 902 is configured tocalculate the blood vessel direction reflected by the result of theprevious frame persistence. The offset module 904 is configured tooffset the result of previous frame persistence along the vesseldirection with the flow direction and the flow velocity. Theinterpolation module 906 is configured to interpolate points in the flowregion having no value after offset. The persistence module 908 isconfigured to carry out an operation of frame persistence between thecurrent flow velocity image and the frame persistence result of theprevious frame which has been offset. In an embodiment, the thirdcomputation module 902 is configure for calculating the blood vesseldirection with gradient properties, wherein the gradient properties areabout the velocity or energy at the center of blood vessel is higherthan that at the both sides and degression on both sides in velocityimage or energy image. In another embodiment, the offset module 904 isconfigured to decompose the offset of the points in the velocity imagealong vertical and horizontal directions respectively based on the bloodvessel direction, and offset the point with a horizontal and verticaloffset along the flow direction, implementing the offset of the framepersistence of the previous frame.

As illustrated in FIG. 10, a system for calculating the blood vesseldirection on a flow velocity image comprises a first distinguishingmodule 1000, an estimation module 1002, a determination module 1004, anda first computation module 1006. The first distinguishing module 1000 isconfigured to distinguish the points in the flow region and points inthe background from a flow velocity image. The estimation module 1002 isconfigured to set a plurality of directions, respectively calculate thenumber of the points in the flow region connecting with the computingpoint in each direction, and take the direction with the maximum numberas the rough direction of the computing point. The determination module1004 is configured to determine midpoints on the direction vertical tothe rough direction in a neighborhood, and take the line connecting themidpoints as the median line of the blood vessel in the neighborhood,wherein the neighborhood takes the computing point as the center andconsists of a plurality of points in the flow region on the roughdirection. The first calculation module 1006 is configured to calculatethe direction of the blood vessel on the computing point according tothe determined median line of the blood vessel. In one embodiment, theimage is binarized by marking the points whose value are smaller than apredefined threshold as zero and the remaining points as 1, thusdistinguishing the points in the flow region and the points in thebackground region.

As illustrated in FIG. 11, a system for calculating the blood vesseldirection on the flow velocity image comprises a second distinguishingmodule 1100, an extraction module 1102, and a second computation module1104. The second distinguishing module 1100 is configured to distinguisheach of the points in the flow velocity image into points in the flowregion and points in the background region. The extraction module 1102is configured to extract the skeleton of the flow region from thedistinguished image. The second calculation module 1104 is configured tocalculate the direction of each point of the skeleton according to aplurality of neighbor points of each computing point of the skeleton,wherein the direction of point of the skeleton is regarded as thedirection of points not on the skeleton, and wherein the point of theskeleton is nearest to the points not on the skeleton and can be linedup in the flow region in the distinguished image.

According to the aforesaid embodiments of the disclosure, a system forcolor flow dynamic frame persistence and a system for calculating bloodvessel direction in a flow velocity image can be realized in a colorultrasonic imaging system with hardware, software, firmware or theircombination.

While specific embodiments and applications of various methods anddevices have been illustrated and described, it is to be understood thatthe invention claimed hereinafter is not limited to the preciseconfiguration and components disclosed. Various modifications, changes,and variations apparent to those of skill in the art may be made in thearrangement, operation, and details of the methods and systemsdisclosed. Additionally, the terms mentioned in the claims and/ordescriptions, such as “first”, “second”, “third”, etc., are used forconvenience and should not be construed as limiting.

Furthermore, the methods disclosed herein comprise one or more steps oractions for performing the described method. The method steps and/oractions may be interchanged with one another. In other words, unless aspecific order of steps or actions is required for proper operation ofthe embodiment, the order and/or use of specific steps and/or actionsmay be modified without departing from the scope of the invention asclaimed.

The embodiments disclosed may include various steps, which may beembodied in machine-executable instructions to be executed by ageneral-purpose or special-purpose computer or other electronic device.Alternatively, the steps may be performed by hardware components thatcontain specific logic for performing the steps, or by any combinationof hardware, software, and/or firmware.

Embodiments of the present invention may also be provided as a computerprogram product including a non-transitory machine-readable mediumhaving stored thereon instructions that may be used to program acomputer (or other electronic device) to perform processes describedherein. The machine-readable medium may include, but is not limited to,floppy diskettes, optical disks, CD-ROMs, DVD-ROMs, ROMs, RAMs, EPROMs,EEPROMs, magnetic or optical cards, or other type ofmedia/machine-readable medium suitable for storing electronicinstructions.

Those of skill in the art would further appreciate that the variousillustrative logical blocks, modules, circuits, and algorithm stepsdescribed in connection with the embodiments disclosed herein may beimplemented as electronic hardware, computer software, or combinationsof both. To illustrate the interchangeability of hardware and software,various illustrative components, blocks, modules, circuits, and stepshave been described above generally in terms of their functionality.Whether such functionality is implemented as hardware or softwaredepends upon the particular application and design constraints imposedon the overall system. Skilled artisans may implement the describedfunctionality in varying ways for each particular application, but suchimplementation decisions should not be interpreted as causing adeparture from the scope of the invention as claimed hereinafter.

What is claimed is:
 1. An image processing method for calculating bloodvessel direction of a flow velocity image comprising a plurality ofpoint-regions, each point-region associated with a central point, themethod comprising: distinguishing each of the point-regions in the flowvelocity image as point-regions in a flow region and point-regions in abackground region; estimating a rough direction of a computingpoint-region by: setting a plurality of directions and respectivelycalculating the number of point-regions in the flow region connectingwith the computing point-region in each direction; and taking thedirection with the maximum number of point-regions as the roughdirection of the computing point-region; determining middlepoint-regions on the direction perpendicular to the rough direction in aneighborhood; determining a line connecting the central points of themiddle point-regions as a median line of the blood vessel in theneighborhood, wherein the neighborhood is centered on the computingpoint-region and includes a plurality of point-regions in the flowregion in the rough direction; and calculating the direction of theblood vessel on the computing point-region according to the determinedmedian line of the blood vessel, wherein calculating comprises applyinga linear fitting or Hough Transform to the determined median line of theblood vessel.
 2. The method of claim 1, wherein distinguishing comprisesbinarizing the image by marking the point-regions whose values aresmaller than a predefined threshold as zero and the remainingpoint-regions as one, thereby distinguishing the point-regions in theflow region and the point-regions in the background region.
 3. Themethod of claim 1 wherein the plurality of directions is selected fromthe group consisting of two directions, or four directions, and eightdirections.
 4. The method of claim 3, wherein the plurality ofdirections is selected from the group consisting of a set of directionscomprising horizontal and vertical directions, and a set of directionscomprising 0°, 45°, 90° and 135°.
 5. A system for calculating bloodvessel direction of a flow velocity image comprising a plurality ofpoint-regions, each point-region associated with a central point, thesystem comprising: a processor; a distinguishing module configured todistinguish each of the point-regions in the blood flow velocity imageas point-regions in a flow region and point-regions in a backgroundregion; an estimation module configured to set a plurality of directionsand respectively calculate the number of the point-regions in the flowregion connecting with a computing point-region each direction, and takethe direction with the maximum number as the rough direction of thecomputing point-region; a determination module configured to determinemiddle point-regions on the direction perpendicular to the roughdirection in a neighborhood; determining a line connecting the centralpoints of the middle point-regions as a median line of the blood vesselin the neighborhood, wherein the neighborhood takes the computingpoint-region as a center point-regions and comprises a plurality ofpoint-regions in the flow region in the rough direction; and acomputation module configured to calculate the direction of the bloodvessel on the computing point-region according to the determined medianline of the blood vessel, wherein the computation module is configuredto applying a linear fitting or Hough Transform to the determined medianline of the blood vessel.
 6. The system of claim 5, wherein the firstdistinguishing module is configured to binarize the image by marking thepoint-regions whose values are smaller than a predefined threshold aszero and the remaining point-regions as 1, thereby distinguishing thepoint-regions in the flow region and the point-regions in the backgroundregion.
 7. The system of claim 5, wherein the plurality of directionscomprises two directions, or four directions, or eight directions.
 8. Anon-transitory computer-readable medium comprising program code thatcauses a processor to perform operations for calculating blood vesseldirection of a flow velocity image comprising a plurality ofpoint-regions, each point-region associated with a central point, theoperations comprising: distinguishing each of the point-regions in theflow velocity image as point-regions in a flow region and point-regionsin a background region; estimating a rough direction of a computingpoint-region by setting a plurality of directions and respectivelycalculating the number of point-regions in the flow region connectingwith the computing point-region in each direction, and taking thedirection with the maximum number of point-regions as the roughdirection of the computing point-region; determining middlepoint-regions on the direction perpendicular to the rough direction in aneighborhood; determining a line connecting the central points of themiddle point-regions as a median line of the blood vessel in theneighborhood, wherein the neighborhood is centered around the computingpoint-region and includes a plurality of point-regions in the flowregion in the rough direction; and calculating the direction of theblood vessel on the computing point-region according to the determinedmedian line of the blood vessel, wherein calculating comprises applyinga linear fitting or Hough Transform to the determined median line of theblood vessel.